Automatic Approach for Cervical Cancer Detection Based on Deep Belief Network (DBN) Using Colposcopy Data

Novitasari, Dian Candra Rini and Foeady, Ahmad Zoebad and Thohir, Muhammad and Arifin, Ahmad Zaenal and Niam, Khoirun and Asyhar, Ahmad Hanif (2020) Automatic Approach for Cervical Cancer Detection Based on Deep Belief Network (DBN) Using Colposcopy Data. In: 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 19 - 21 Februari 2020, Fukuoka, Japan.

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Abstract

Cervical cancer is one of the diseases with the
highest mortality rate. In the world, cervical cancer is ranked as the fourth most dangerous disease. Based on these problems,this paper can be an alternative to help medical authorities in detecting cervical cancer with the help of the Computer-Aided Diagnosis (CAD) System. CAD System used has two processes,such as preprocessing and classification. Preprocessing is useful to improve the image so that it is easier to do the process of identifying features. Preprocessing used is greyscale, histogram equalization, and median filter. Preprocessing results will be formed into a vector matrix using the reshaping process. The final step is the process of classifying data using the Deep Belief
Network method. The best accuracy results obtained from the
identification process of cervical cancer using the DBN method is 84%. Based on the results of accuracy, is expected to help reduce the number of deaths from cervical cancer with early detection

Item Type: Conference or Workshop Item (Paper)
Creators:
Creators
Email
["eprint_fieldname_creators_NIDN" not defined]
Novitasari, Dian Candra Rini
diancrini@uinsby.ac.id
2024118502
Foeady, Ahmad Zoebad
UNSPECIFIED
UNSPECIFIED
Thohir, Muhammad
muhammadthohir@uinsby.ac.id
2025077402
Arifin, Ahmad Zaenal
-
UNSPECIFIED
Niam, Khoirun
khoirunniam@uinsby.ac.id
2025077001
Asyhar, Ahmad Hanif
hanif@uinsby.ac.id
UNSPECIFIED
Subjects: 09 ENGINEERING > 0912 Materials Engineering > 091299 Materials Engineering not elsewhere classified
Divisions: Fakultas Sains dan Teknologi > Prodi Matematika
Depositing User: Ummi Rodliyah
Date Deposited: 18 Jan 2022 09:23
Last Modified: 18 Jan 2022 09:23
URI: http://repository.uinsa.ac.id/id/eprint/1982

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